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Computational Methods and GIS Applications in Social Science - Textbook and Lab Manual [Multiple-component retail product]

, (Louisiana State University, Baton Rouge, USA)
  • Formaat: Multiple-component retail product, 724 pages, kõrgus x laius: 234x156 mm, kaal: 1620 g, 51 Tables, black and white; 74 Line drawings, color; 35 Line drawings, black and white; 237 Halftones, color; 311 Illustrations, color; 35 Illustrations, black and white, Contains 1 Hardback and 1 Paperback / softback
  • Ilmumisaeg: 26-Oct-2023
  • Kirjastus: CRC Press
  • ISBN-10: 1032285184
  • ISBN-13: 9781032285184
Teised raamatud teemal:
Computational Methods and GIS Applications in Social Science - Textbook and Lab ManualSuurem pilt
  • Formaat: Multiple-component retail product, 724 pages, kõrgus x laius: 234x156 mm, kaal: 1620 g, 51 Tables, black and white; 74 Line drawings, color; 35 Line drawings, black and white; 237 Halftones, color; 311 Illustrations, color; 35 Illustrations, black and white, Contains 1 Hardback and 1 Paperback / softback
  • Ilmumisaeg: 26-Oct-2023
  • Kirjastus: CRC Press
  • ISBN-10: 1032285184
  • ISBN-13: 9781032285184
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781032285184.html
Märksõnad:

This set integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of spatial social science with step-by-step instructions in ArcGIS Pro and open-source platform KNIME.



The textbook and lab manual integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of spatial computational social science and includes numerous new examples and case studies with step-by-step instructions in ArcGIS Pro and open-source platform KNIME. KNIME supports visual programming and multiple scripting language such as R, Python, and Java. It helps readers sharpen their GIS skills by applying GIS techniques in detecting spatiotemporal crime hot spots, measuring accessibility of primary care physicians, forecasting the impact of hospital closures on local community, or siting the best locations for business.

Features

· Fully updated using the latest version of ArcGIS Pro and open-source platform KNIME

· Includes many compelling examples and real-world case studies related to social science, urban planning, and public policy with clear step-by-step instructions

· Provides newly automated programs for regionalization, functional region delineation, accessibility measures, maximal accessibility equality problem, and agent-based crime simulation

· Includes 22 case studies from USA and China that parallel the methods developed in the textbook and enable readers to easily replicate and expand their work

· Adds two new chapters on agent-based modeling and big data analytics

This set is intended for upper-level undergraduate and graduate students taking courses in quantitative geography, spatial analysis, GIS applications in socioeconomic studies, GIS applications in business, location theory. Researchers in similar fields: geography, city and regional planning, sociology, criminology, public health, and public administration.

Textbook

Part I: GIS and Basic Spatial Analysis Tasks
1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools
2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior
3. Spatial Smoothing and Spatial Interpolation Part II: Basic Computational Methods and Applications
4. Delineating Funcational Regions and Applications in Health Geography
5. GIS-bAsed Measures of Spatial Accessibility and Application in Examining Healthcare Disparity
6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns
7. Principal Compnents, Factor and Cluster Analyses and Application in Social Area Analysis
8. Spatial Statistics and Applications inCultural and Crime Geography
9. Regionalization Methods and Application in Analysis of Cancer Data Part III: Advanced Computational Methods and Applications
10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns
11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers
12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations
13. Agent-Based Model and Application in Crime Simulation
14. Spatiotemporal Big Data Analytics and Application in Urban Studies

Lab Manual

1. Getting Started with KNIME and Its Geospatial Analytics Extension
2. Measuring Distance and Time and Analyzing Distance Decay Behavior
3. Spatial Smoothing and Spatial Interpolation
4. Delineating Functional Regions and Application in Health Geography
5. GIS-Based Measure of Spatial Accessibility and Application in Examining Healthcare Disparity
6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns
7. Principal Components, Factor Analysis and Cluster Analysis and Application in Social Area Analysis
8. Spatial Statistics and Applications
9. Regionalization Methods and Applications in Analysis of Cancer Data
10. System of Linear Equations and Application of Garin-Lowry Model in Simulating Urban Population and Employment Patterns
11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers
12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations
13. Agent-Based Model and Application in Crime Simulation
14. Spatiotemporal Big Data Analytics and Applications in Urban Studies

Fahui Wang is Associate Dean of the Pinkie Gordon Lane Graduate School and Cyril & Tutta Vetter Alumni Professor in the Department of Geography and Anthropology, Louisiana State University. He earned a BS degree in geography from Peking University, China, and an MA degree in economics and a PhD in city and regional planning from the Ohio State University. His research has revolved around the broad theme of spatially integrated computational social sciences, public policy and planning in Geographic Information Systems. He is among the top 1% most-cited researchers in geography in the world.

Lingbo Liu is a postdoctoral fellow at the Center for Geographic Analysis, Harvard University, leading the development of Geospatial Analytics Extension for KNIME. He was a lecturer at the Department of Urban Planning, School of Urban Design, Wuhan University from 2005 to 2022, and obtained his PhD in Digital Urban Administration and Planning from Wuhan University in 2018. His research uses multi-source data and quantitative models to capture the spatiotemporal features of urban systems, and provides decision support for public policy, sustainable urban planning, and design.